Create a Q-Q plot of the test statistics. The x-axis has the
theoretical quantile you would expect from a standard normal distribution.
The y-axis has the observed quantiles. In the Wald case, it is a ggplot2 version of
what you would get from qqnorm and qqline.
plot_qq(obj, test, test_type = "wt", which_model = "full",
sig_level = 0.1, point_alpha = 0.2, sig_color = "red",
highlight = NULL, highlight_color = "green", line_color = "blue")a sleuth object
a character string denoting which beta to use for highlighting the transcript
either 'wt' for wald test or 'lrt' for likelihood ratio test.
a character string denoting which model to use for the test
the significance level for Fdr
the alpha for the points
what color to make the 'significant' transcripts
a data.frame with one column, target_id.
These points will be highlighted in the plot. if NULL, no points will
be highlighted.
the color to highlight points.
what color to make the QQ line
a ggplot2 object